Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
- (pp. 77-82)
(Complimentary)
Abstract
Data from digital platforms have the potential to improve our understanding of gentrification, both by predicting gentrification and by characterizing the local economy of gentrifying neighborhoods. To explore, we identify gentrifying neighborhoods using government data, and then use Yelp data to analyze local business activity. We find that gentrifying neighborhoods tend to have growing numbers of local groceries, cafes, restaurants, and bars, with little evidence of crowd-out of other types of businesses. Moreover, local economic activity, as measured by Yelp data, is a leading indicator for housing price changes and can help to predict which neighborhoods are gentrifying.Citation
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. 2018. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings, 108: 77-82. DOI: 10.1257/pandp.20181034Additional Materials
JEL Classification
- C53 Forecasting Models; Simulation Methods
- C83 Survey Methods; Sampling Methods
- R11 Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
- R23 Urban, Rural, Regional, Real Estate, and Transportation Economics: Regional Migration; Regional Labor Markets; Population; Neighborhood Characteristics
- R31 Housing Supply and Markets
- R32 Other Spatial Production and Pricing Analysis
- R58 Regional Development Planning and Policy